UBIOES-DM : Biostatistics and data management unit
GINYS-ISGLOBAL-002
The Biostatistics and Data Management facility (UBIOES-DM) provides scientists with complete consultancy services on statistics and data management for their research projects at all developmental stages.
The use of statistics in a research project is based on two main pillars: the ethic of the statisticians involved in implementing the most appropriate statistical approaches to a given set of data, and the quality of those data. To ensure that both aspects are always taken into consideration, the UBIOES-DM integrates experienced statisticians and data managers that can offer both statistical and data management support from a braod perspective, always adpating to the needs and specific requirements of each project. Currently the UBIOES-DM is composed by four statisticians and three data managers, and can offer both ad-hoc advising and comprehensive support on statistics and data management.
Services
1. Comprehensive data management support: Guidance in selecting appropriate and secure data collection and management systems and methods. Configuration and tuning of open-source software (OpenClinica, ODK, REDCap, etc.) to meet special data analysis or study design needs. Database design and development of web interface applications or extensions to manage data. Questionnaire and tools review (electronic or paper-based, surveys). Data quality procedures definition. Data management plan, data cleansing plans and documentation support. Programming of own tools adapted to each project to ensure the proper project’s follow up.
2. Comprehensive statistical support/data analysis: Statistical support during all project’s developmental stages: from the project request stage (eg sample calculation, study design, drafting of statistical methods of the proposal or study protocol, …), to intermediate stages (eg drafting of the SAP, statistical analysis, creation of the final report of the analysis with the necessary tables / graphs, …), and up to the final stages of scientific projects (eg writing of the scientific article, response to the reviewers of the journal, …).
Final data curation, in collaboration with the data management team, with the objective of making research data findable, accessible, interoperable and reusable (FAIR).
3. Ad-hoc advising: Solving methodological doubts in statistical analysis and data management. Under this modality, the facility provides advice, but all required processes are taken care of by the personnel of each research project (and not by the facility).
4. Training: Possibility to offer personalized courses on statistics fundamentals and data management.
Equipment
